%0 Journal Article %1 journals/spm/GribonvalCKSJS21 %A Gribonval, Rémi %A Chatalic, Antoine %A Keriven, Nicolas %A Schellekens, Vincent %A Jacques, Laurent %A Schniter, Philip %D 2021 %J IEEE Signal Process. Mag. %K dblp %N 5 %P 12-36 %T Sketching Data Sets for Large-Scale Learning: Keeping only what you need. %U http://dblp.uni-trier.de/db/journals/spm/spm38.html#GribonvalCKSJS21 %V 38

@article{journals/spm/GribonvalCKSJS21, added-at = {2021-09-16T00:00:00.000+0200}, author = {Gribonval, Rémi and Chatalic, Antoine and Keriven, Nicolas and Schellekens, Vincent and Jacques, Laurent and Schniter, Philip}, biburl = {https://www.bibsonomy.org/bibtex/284a94dbf3ebe1286effba6f7e73c89f6/dblp}, ee = {https://doi.org/10.1109/MSP.2021.3092574}, interhash = {5669d591ddf376d13b7baecdd6f0dd23}, intrahash = {84a94dbf3ebe1286effba6f7e73c89f6}, journal = {IEEE Signal Process. Mag.}, keywords = {dblp}, number = 5, pages = {12-36}, timestamp = {2024-04-09T02:30:38.000+0200}, title = {Sketching Data Sets for Large-Scale Learning: Keeping only what you need.}, url = {http://dblp.uni-trier.de/db/journals/spm/spm38.html#GribonvalCKSJS21}, volume = 38, year = 2021 }